逻辑回归
医学
单变量
人工神经网络
认知
多元统计
认知障碍
多元分析
预测建模
机器学习
计算机科学
内科学
精神科
作者
Xinran Zhu,Shumei Zhuang,Xueying Zhou,Linan Wang,Ying Guo,Peng Wang,Hou Yahong,Ma Longting,Jing Wang
摘要
The purpose of this study was to identify risk factors for cognitive impairment in advanced cancer patients and to develop predictive models based on these risk factors.Cancer-related cognitive impairment seriously affects the quality of life of advanced cancer patients. However, neural network models of cognitive impairment in patients with advanced cancer have not yet been identified.A cross-sectional design was used.This study collected 494 questionnaires between January and June 2022. Statistically significant clinical indicators were selected by univariate analysis, and the artificial neural network model and logistic regression model were used for multivariate analysis. The predicted value of the model was estimated using the area under the subject's working characteristic curve.The artificial neural network and the logistic regression models suggested that cancer course, anxiety and age were the major risk factors for cognitive impairment in advanced cancer patients. All the indexes of artificial neural network model constructed in this study are better than those of the logistic model.The artificial neural network model can better predict the risk factors of cognitive impairment in patients with advanced cancer. Better prediction will enable nurses and other healthcare professionals to provide better targeted and timely support.
科研通智能强力驱动
Strongly Powered by AbleSci AI